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Env And Assets Bootstrap

  • 29 installs
  • 512 repo stars
  • Updated July 26, 2026
  • lllllllama/ai-paper-reproduction-skills

This is a copy of env-and-assets-bootstrap by lllllllama - installs and ranking accrue to the original listing.

Helps with ai & agent building tasks.

About

env-and-assets-bootstrap is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted development.

  • env-and-assets-bootstrap
  • AI & Agent Building
  • AI-coding skill

Env And Assets Bootstrap by the numbers

  • 29 all-time installs (skills.sh)
  • Data as of Aug 3, 2026 (Skillselion catalog sync)
npx skills add https://github.com/lllllllama/ai-paper-reproduction-skills --skill env-and-assets-bootstrap

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Listed on Skillselion
Installs29
repo stars512
Last updatedJuly 26, 2026
Repositorylllllllama/ai-paper-reproduction-skills

What it does

Helps with ai & agent building tasks.

Files

SKILL.mdMarkdownGitHub ↗

env-and-assets-bootstrap

Use this as the Rigor Setup skill. The installed slug remains env-and-assets-bootstrap for compatibility.

Use the shared operating principles in ../../references/agent-operating-principles.md; this skill should keep setup planning conservative while leaving environment-specific judgment to the model.

When to apply

  • After repo intake identifies a credible reproduction target.
  • When environment creation or asset path preparation is needed before running commands.
  • When the repo depends on checkpoints, datasets, or cache directories.
  • When the user explicitly wants setup help before any run attempt.

When not to apply

  • When the repository already ships a ready-to-run environment that does not need translation.
  • When the task is only to scan and plan.
  • When the task is only to report results from commands that already ran.
  • When the request is a generic conda or package-management question outside repo reproduction.

Clear boundaries

  • This skill prepares environment and asset assumptions.
  • It does not own target selection.
  • It does not own final reporting.
  • It does not perform paper lookup except by forwarding gaps to the optional paper resolver.

Input expectations

  • target repo path
  • selected reproduction goal
  • relevant README setup steps
  • any known OS or package constraints

Output expectations

  • conservative environment setup notes
  • candidate conda commands
  • asset path plan
  • checkpoint and dataset source hints
  • unresolved dependency or asset risks

Notes

Use references/env-policy.md, references/assets-policy.md, scripts/bootstrap_env.py, scripts/plan_setup.py, and scripts/prepare_assets.py. Use scripts/bootstrap_env.sh only as a POSIX wrapper around the Python bootstrapper when a shell entrypoint is more convenient.

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